Huy H. Nguyen

Huy H. Nguyen

Specially Appointed Assistant Professor at the National Institute of Informatics, Tokyo, Japan.

Welcome

I am Huy H. Nguyen (Nguyễn Hồng Huy in Vietnamese).

I am currently a specially appointed assistant professor (特任助教) at Echizen Laboratory, National Institute of Informatics, Tokyo, Japan. My research interests include security and privacy in biometrics and machine learning, plus fake media generation and detection.

I received my BS. degree (honors program) from VNUHCM - University of Science, Vietnam, in 2013, and my Ph.D. degree from The Graduate University for Advanced Studies, SOKENDAI in alliance with the National Institute of Informatics, Japan, in 2022.

For more details, please have a look at my CV here (last update: Oct. 10, 2024).

Selected News

  1. Three deepfake papers were accepted to IJCB 2024.
  2. Two papers (spurious feature generation, defense against physical adversarial attacks on infrared domain) were accepted to ICIP 2024.
  3. Two papers (eKYC-Deepfake dataset and a comparative study of fine-grained counting methods) were published in IEEE Access.
  4. A paper about watermarking for LLMs was accepted to ICASSP 2024.
  5. Two NLP papers (detecting academic AI text and multimodal out-of-context detection) were accepted to AINA 2024.
  6. Our pioneer work on deepfake restoration, namely Cyber Vaccine, was published in IEEE Access.
  7. Our work on measuring the similarities between other computer vision tasks to deepfake detection was accepted to IJCB 2023 (arXiv).
  8. Our collaborative paper on physics-based adversarial attack on near-infrared human detector with Oscars Lab at the University of Tokyo was accepted to ACM Multimedia 2023 (DOI, implementation).
  9. Our paper on adversarial image purification was accepted to IEEE Open Journal of Signal Processing (paper, source code will be published soon).
  10. Two papers were accepted to WACV 2023. One is about master vein attacks on finger vein recognition systems (arXiv); the other is about the theory of the non-robust features on the transferability of adversarial examples (arXiv).
  11. Our work on applying adversarial machine learning for privacy protection was accepted to WIFS 2022. Another work on the same topic was previously published in CVPRW 2021.
  12. Our premier work on master faces was published in IJCB 2020 (arXiv) and IEEE T-BIOM (arXiv)
  13. Our book chapters on deepfake detection were published in Handbook of Digital Face Manipulation and Detection - From DeepFakes to Morphing Attacks (implementation) and Frontiers in Fake Media Generation and Detection.
  14. Our paper on the OpenForensics dataset was published in ICCV 2021 (implementation).
  15. Our early work on deepfake detection and segmentation was published in ICASSP 2019 (arXiv, implementation) and BTAS 2019 (arXiv, implementation).

Academic Activities

  1. Reviewer:
    • Conferences: NeurIPS, ICLR, ICML, CVPR, ECCV, WACV, ICME, ACL RR, APSIPA ASC.
    • Journal: IEEE (Access, TIP, TIFS), IEEE/CAA JAS, ACM TOMM, Elsevier (PRLETTERS, EAAI), EURASIP JIVP, IEICE.
  2. Session Chair:
    • APSIPA ASC 2020 Special Session: Deep Generative Models for Media Clones and Its Detection.
    • APSIPA ASC 2023 Special Session: Multimedia Security and Privacy in the Age of Deep Learning.

Contact

Please contact me at

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